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Force-directed graph drawing algorithms assign forces among the set of edges and the set of nodes of a graph drawing.Typically, spring-like attractive forces based on Hooke's law are used to attract pairs of endpoints of the graph's edges towards each other, while simultaneously repulsive forces like those of electrically charged particles based on Coulomb's law are used to separate all pairs ...
An embedded graph uniquely defines cyclic orders of edges incident to the same vertex. The set of all these cyclic orders is called a rotation system.Embeddings with the same rotation system are considered to be equivalent and the corresponding equivalence class of embeddings is called combinatorial embedding (as opposed to the term topological embedding, which refers to the previous ...
OLE 1.0, released in 1990, was an evolution of the original Dynamic Data Exchange (DDE) concept that Microsoft developed for earlier versions of Windows.While DDE was limited to transferring limited amounts of data between two running applications, OLE was capable of maintaining active links between two documents or even embedding one type of document within another.
In databases, brushing and linking is the connection of two or more views of the same data, such that a change to the representation in one view affects the representation in the other. [1] Brushing and linking is also an important technique in interactive visual analysis , a method for performing visual exploration and analysis of large ...
[1] [4] For small values of , the edge rectangles become long and thin like ribbons, giving the name to the representation. In the other direction, from a ribbon graph one may find the faces of its corresponding embedding as the components of the boundary of the topological surface formed by the ribbon graph.
An embedding, or a smooth embedding, is defined to be an immersion that is an embedding in the topological sense mentioned above (i.e. homeomorphism onto its image). [ 4 ] In other words, the domain of an embedding is diffeomorphic to its image, and in particular the image of an embedding must be a submanifold .
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The machine learning task for knowledge graph embedding that is more often used to evaluate the embedding accuracy of the models is the link prediction. [ 1 ] [ 3 ] [ 5 ] [ 6 ] [ 7 ] [ 18 ] Rossi et al. [ 5 ] produced an extensive benchmark of the models, but also other surveys produces similar results.
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